The main objective of this project is to empirically analyze the impact of built attributes on greenhouse gas (GHG) emissions caused by urban mobility in the context of Québec. This research is carried out using the origin/destination (O-D) surveys for the regions of Montréal, Québec and Sherbrooke. Moreover, by combining the data from the 1998, 2003 and 2008 origin-destination surveys for Montréal allow for better control for self-selection bias. The specific objectives of our research are to: i) Develop and apply a methodology to estimate GHG emissions using completely disaggregated trip data and taking into account all emitting modes; ii) Develop a modeling framework to estimate the impact of the factors affecting household GHG emissions. The factors to be tested include individual and household socioeconomic attributes (e.g. age, income), car ownership, urban form (UF) and transit supply (TS) attributes (reefed also as built environment – BE) around the respondent's dwelling. For Montréal downtown commuters, the costs of different transportation modes (e.g. parking prices, travel times, transit fares, etc.) are also evaluated; iii) To apply the empirical results for estimating the potential GHG reductions of different policy initiatives and scenarios such as, the development of compact neighborhoods, transit accessibility investments and technological improvements.

Among the results, it was found that land use mix, population density and public transit accessibility have statistically significant and negative effects on household GHGs and other travel outcomes such as, car distance, activity spaces and commuter mode choices. This is in accordance with the literature; however, the elasticities obtained for Montréal are greater than those obtained in past studies and the other two study regions (Québec and Sherbrooke). Moreover, the results demonstrate that the effects of built environment can vary considerably across subgroups (household subpopulations). This suggests that different household subgroups can respond differently to changes in the built environment. When looking at the whole Montréal household population, it is observed that the average household GHGs have slightly declined during the analysis period (1998-2008). This reduction can be associated to both the reduction in car usage (car distance) and the fuel efficiency improvements of the automobile fleet over the last few years. From the comparative analysis among the three regions it is observed that important GHG variations exist between neighborhoods, which are much greater than the GHGs variations between cities. That is, the carbon generation of households located in central neighborhoods is 3-4 times greater on average than carbon generated by households in outer suburbs. These variations are much higher than those observed on average between cities. This result is confirmed with the elasticity analysis that also confirms the important impact of neighborhood typologies, after controlling for socio-demographics.

Regarding the socio-demographic factors and their link to household GHGs, the factors found to be positively associated with GHGs where the number of full-time and part-time workers as well as students generating commuting travel. However, presence of the retirees and children are negatively associated with GHGs. Other salient variables are income and vehicle car ownership, which are expected to play an important role in the household and regional emission inventories, showing the importance of the regional economy, which might have important implications in terms of fuel demand, car usage and car ownership.

Regarding the analysis of determinants of mode choice for downtown commuters in Montréal, it is found that both transit mode attributes and parking costs appear to have significant effects on the transportation mode choice of downtown commuters. In addition, increasing public transit (PT) travel time and fares negatively affect the use of PT, while raising the cost of parking increases the probability of choosing PT. Again, the neighborhood type where commuters live plays also an important role in the mode choice even after controlling for sociodemographics and transit attributes.

Finally, this study compares and estimates the impact of technological scenarios with BE strategies. The results show that changing current transit buses and/or trains (in the case of Montréal) to hybrid buses/electric trains would have only a marginal impact on the total GHGs emitted at the household level given that the percentage of transit emissions from the total is already very low (e.g., less than 4% for Montréal). However, when projecting the fuel efficiency of the motorvehicle fleet to the year 2020, one can see that important reductions could be expected for the three regions, for instance 7% for Montréal. This highlights the important role that the fuel efficiency trends of Québec's automobile fleet will play in the short future.

Finally, the combination of BE and technological scenarios are elaborated for the city of Montréal. A BE scenario is generated based on population density trends in the previous years (10 years) in order to predict the population density for the horizon year (2020). Combining these projects with elasticities, the expected impact of changes in the population density would translate into a reduction of 3.2% in the household GHGs for the year 2020. Despite their potential benefits, the changes of the BE are less dynamic over time which would indicate that only the combination of both technological and built environment strategies would be sufficient to reach significant carbon reductions for the year 2020.

The main members of the team are Luis Miranda-Moreno (McGill University), Philippe Barla (Université Laval) and Zachary Patterson (Concordia University). The team collaborators include Martin Lee-Gosselin (Université Laval), Marie-Soleil Cloutier (INRS) and N. Luka (McGill University).